Preferred Modes of Variability and Their Relationship with Climate Change

1. Preferred Modes of Variability and Their Relationship with Climate Change Seok-Woo Son and Sukyoung Lee The Pennsylvania State University Department of Meteorology

2. Annular Mode - Dominant internal variability of the atmosphere SH NH • Leading EOF of SLP [u] • Zonally symmetric • Quasi-barotropic • Useful for understanding internal variability SLP • Useful for understanding climate change (?) Thompson et al. 2000

3. SH [u] response to global warming NH [u] trend 1968-1997 pressure (hPa) NH Annular Mode SH Annular Mode pressure (hPa) latitude Thompson et al. 2000 Kushner et al. 2001

4. “Spatial pattern” of annular mode ≈ recent trend in the observed and simulated zonal-mean circulation To what extent annular mode is capable of predicting zonal-mean climate change?

5. Total 49 simulations by differing radiative heating in a simple GCM Structure of [u] in the statistically steady state ( [u] ) Internal variability of [u] with a help of EOF1 and EOF2 Annular mode vs. Climate change Annular mode – EOF1 of [u] (regressed against PC1 time series) Climate change – difference of [u] between any two adjacent runs Purpose and Approaches Evaluate the predictability of zonal-mean climate change by annular mode in terms of their spatial structures.

6. Te(C,H) = Tbase + ΔTe(C,H) C : high-latitude cooling (K/day) H : tropical heating (K/day) Numerical Model • A dynamic core of GFDL GCM (symmetric boundary cond.) • R30L10 but zonal wave number 15 • Driven by relaxing T toward Te with timescale of 30 days • Dissipated by linear friction and 8th order hyperdiffusion

7. (C,H)=(0.83,0.33) (C,H)=(0.17,1.67) (C,H)=(0.17,0.33) [u] Double Jet Intermediate Jet Single Jet Numerical Model (Cont.) • Total 49 realizations C (0.00, 0.17, 0.33, 0.50, 0.67, 0.88, 1.00) K/day H (0.00, 0.33, 0.67, 1.00, 1.33, 1.67, 2.00) K/day • Statistics are derived from the last 4500 days of each 5000-day integration. Data of both hemispheres are used.

8. [u] : Structure of Westerly Jets • Strong C & weak H → Double Jet SJ • H ≥ 1.00K/day → Single Jet WJ DJ

9. Internal variability of the jets [u] & EOFs One-point correlation of 250-hPa [u]' Zonal-index (Jet Meander) SJ WJ Transition Poleward Propagation DJ

10. Time series of PC1 and PC2 Correlation PC1 vs. PC2 Zonal-index (Jet Meander) SJ Transition WJ Poleward Propagation DJ Poleward Propagation: i. Correlation between PC1 & PC2 is very high ii. Var(EOF2) is comparable to Var(EOF1)

11. Collocates with intermediate- and double-jet Shading χ≥ 0.5 Shading γ≥ 0.5

12. Climate change : Difference of [u] between two adjacent runs • δ[u]H (0.50,1.00) = [u] (0.50,1.33) - [u] (0.50,1.00) • δ[u]C (0.50,1.00) = [u] (0.67,1.00) - [u] (0.50,1.00) [u] (0.50,1.00) δ[u]H (0.50,1.00) δ[u]C (0.50,1.00) Annular mode & Climate change in the modeI • Annular mode : EOF1 of [u] • [u] is regressed against PC1 time series, unit of m/s.

13. I. Global measure : pattern correlation between EOF1 and δ[u] from 150-950 hPa and 10-80˚ EOF1 & δ[u]C EOF1 & δ[u]H Predictability of Climate change by Annular mode Shading correlation ≥ 0.8 Predictability is always poor in a poleward propagation regime.

14. Poor predictability ofδ[u]Hin a zonal-index regime • Annular mode in the model is associated with eddy fluxes. • δ[u]Cis associated with eddy fluxes. • δ[u]H is associated with both eddy fluxes and mean-meridional circulation. • Predictability of δ[u]C would be better than that of δ[u]H. • Increase of C → enhances extratropical baroclinicity • Increase of H → enhances subtropical baroclinicity and • intensifies Hadley circulation

15. Structure of Westerly Jet • Strong C & weak H → Double Jet • H ≥ 1.00 K/day → Single Jet Internal Variability • Strong C & weak H → Poleward propagation • (Comparable effect of EOF2) • Weak C & strong H → Zonal index • (Dictated by EOF1) • Broad transition zone Predictability of Climate change by Annular mode • Dependent on the dominant internal variability • Relative good in a transition regime Summary

16. EOF1 & δ[u]H EOF1 & δ[u]C [u]: structure of the jet SH SH SH Application to the Southern Hemisphere • Applied to the SH climate change at equinoctial condition Global warming at SH → ENSO-like tropical heating & enhanced extratropical baroclinicity (Son and Lee 2005a) → increase of H and C. • Structure of the jet Wide range of interannual variability from single- to double-jet states • Internal variability Both poleward propagation and zonal index (e.g., Feldstein 1998; Hartmann and Lo 1998) with γ ≈ 0.5 and χ ≈ 0.3 (Son and Lee 2005b).

17. EOF1 & δ[u]H EOF1 & δ[u]C SH SH Application to the Southern Hemisphere (Cont.) • Predictability is marginally good in the SH-like parameter regime. • Annular mode may not be useful for understanding paleoclimate change. Slight climate drift to the poleward propagation regime → poor predictability.

18. Any comment and suggestion are welcome. Thank you! Contact information Seok-Woo Son: sus141@psu.edu

19. The latitudinal distance over which the value of 250-hPa quasi-geostrophic PV gradient ([q]y) is greater than 60% of its maximum value. Shading for ≥ 35˚. Dependency of internal variability to the mean flow • The meridional radiation of the waves is prohibited if the PV gradient of the ambient flow is sufficiently sharp (e.g., Hoskins and Ambrizzi 1993) • Poleward propagation of westerly anomalies may occur only when the PV gradient is relatively weak and broad.

20. [u] (0.50,100) δ[u]H (0.50,100) δ[u]C (0.50,100) Prediction of Climate-change ‘Direction’ by Annular mode? • Climate change direction (positive or negative phase of annular mode) is determined not by the annular mode but by the nature of external forcing. • Climate change associated with H increase (warming at tropics) →negative phase of annular mode (out of phase). • Climate change associated with C increase (broadening of extratropical baroclinic zone) →positive phase of annular mode (in phase). - +

21. SH [u] response to global warming Climate change in SH is in phase with SH annular mode. SH Annular Mode By the overwhelming effect of enhanced baroclinicity (C) over tropical warming (H) ? Kushner et al. 2001 Prediction of Climate-change ‘Direction’ ? (Cont.) Climate change in SH: tropical warming & enhanced extratropical baroclinicity (Son and Lee 2005a) → increase ofHandC.

22. II. Local measure : latitudinal distance between extrema of EOF1 and δ[u] at 250 hPa EOF1 & δ[u]C(line A) • δφC : between EOF1 and δ[u]C • δφH : between EOF1 and δ[u]H δφC A Predictability of Climate change by Annular mode • measured at both • subtropics and extratropics

23. δφC(mid-latitude) δφC (low-latitude) δφH (low-latitude) δφH (mid-latitude) Shading γ≥ 0.5 Shading δφ≤ 2˚ • Weak latitudinal dependency of δ[u]Cprediction by annular mode. • Poor predictability of δ[u]Hin a zonal-index regime is due to the mid-latitudes. • Predictability is generally good when γ ≤ 0.5 or Var(EOF1) ≥ 2•Var(EOF2)

24. II. Local measure : Compare amplitude of 250-hPa |EOF1| and |δ[u]| at 250 hPa EOF1 & δ[u]C(line A) δφC A Prediction of Climate-change ‘Amplitude’ by Annular mode?

25. shading:δφC ≤ 2˚ shading:δφH ≤ 2˚ ratio |δ[u]|/|EOF1| difference (|δ[u]| - |EOF1|) • Ratios of |δ[u]C| to |EOF1| are 0.3 to 0.8. Ratios vary only by a factor of two! • Ratios of |δ[u]H| to |EOF1| are 1.0 to 2.5 Predictable? No theories yet! Prediction of Climate-change ‘Amplitude’ by Annular mode?